Title :
Content-based recognition of musical instruments
Author :
Fanelli, Anna Maria ; Caponetti, Laura ; Castellano, Giovanna ; Buscicchio, Cosimo Alessandro
Author_Institution :
Dipt. di Informatica, Universita degli Studi di Bari, Italy
Abstract :
A method for content-based audio classification is presented. In particular we focus on identification of musical instruments sounds based on timbre classification, using a biologically plausible features extraction technique called cochleagram, and a new model of recurrent neural network called LSTM. Preliminary experiments are performed to compare various feature sets and neural network sizes. In particular two experiments are performed, using two different feature sets. The best classification rate obtained is 80%, averaged on 20 trials.
Keywords :
audio databases; audio signal processing; content-based retrieval; feature extraction; musical instruments; recurrent neural nets; signal classification; audio classification; audio database; audio feature extraction; content-based recognition; musical instrument; recurrent neural network; Biological system modeling; Content based retrieval; Electronic mail; Feature extraction; Instruments; Music information retrieval; Neural networks; Pattern recognition; Recurrent neural networks; Timbre;
Conference_Titel :
Signal Processing and Information Technology, 2004. Proceedings of the Fourth IEEE International Symposium on
Print_ISBN :
0-7803-8689-2
DOI :
10.1109/ISSPIT.2004.1433794
